Computer simulation can help measure attendance, severity of behavioral problems

The introduction of computer simulation to identify symptoms in children with attention deficit hyperactivity disorder (ADHD) has the potential to provide an additional targeting tool to assess the presence and severity of behavioral problems. measure, Ohio State University researchers suggest in a new publication.

Most mental health problems are detected and treated based on clinical interviews and questionnaires – and, for about a century, data from psychiatric tests have been added to the study process to help clinicians to learn more about how and why people behave in a certain way.

Psychological testing in ADHD is used to identify a number of symptoms and deficits, including selective attention, poor working memory, altered time comprehension, difficulty maintaining attention, and critical behavior. In the most common class of performance tests, children are asked to either press a computer key or avoid hitting a key when they see a word, symbol, or other stimulus.

For ADHD, however, these cognitive tests often do not capture the complexity of the symptoms. The advent of computer psychology – comparing a computer-like model of normal brain processes to intractable processes studied in experiments – could be an important improvement to the diagnostic process for ADHD, Ohio State research reports in a new study published in the journal Journal of Psychology.

The research team reviewed 50 studies of cognitive tests for ADHD and described how three common types of computer models may contribute to these tests.

It is widely recognized that children with ADHD take more time to make decisions while performing the activities of children without the disorder, and tests have relied on to average response times to explain the difference. But there is a complexity to that disorder that a computer model could help identify, providing information that clinicians, parents, and teachers can use to make life easier for children. with ADHD.

“We can use models to simulate the decision-making process and see how decisions happen over time – and work better to find out why children with ADHD take longer to make decisions, “said Nadja Ging – Jehli, lead author of the review, Ohio University, a graduate student in psychology at Ohio State.

Ging-Jehli completed the review with Ohio State faculty members Roger Ratcliff, professor of psychology, and L. Eugene Arnold, professor emeritus of psychology and behavioral health.

The researchers offer recommendations for trial and clinical practice to achieve three main goals: ADHD with a better character and any accompanying mental health studies such as anxiety and depression, improving treatment outcomes (no about one-third of patients with ADHD respond to medical treatment), which may predict which children will “miss” the ADHD diagnosis as adults.

Decisions behind the wheel of a car help highlight the problem: Drivers know that when a red light turns green, they can go through an intersection – but not everyone hit the gas pedal at the same time.

A common mental test of this behavior would again expose drivers to the same green-light light position to arrive at an average response time and use that average, and movements from it, to reverse the normal driver against misbehavior. sorting system.

This approach has been used to confirm that people with ADHD are generally slower to “start driving” than those without ADHD. But that decision leaves out a range of opportunities that help explain why they’re slower – they could be distracted, looking through the day, or ‘feeling anxious in a laboratory setting. The wide distribution of feedback captured by computer modeling could provide more informative and useful information.

“In our review, we show that this approach has a number of problems that prevent us from understanding the underlying features of mental health disorders such as ADHD, and that also prevents us from discovering the best treatment for different individuals, “said Ging-Jehli.

“We can use computer modeling to think about the factors that generate the observed behavior. These factors expand our understanding of disorder, acknowledging that there are different types of people with different deficits who are also wanting different treatments.

“We plan to use a full rotation of the response times, taking into account the slowest and fastest response times to differentiate between different types of ADHD.”

The review also identified a complex feature for ongoing ADHD research – a wider range of external markers as well as subtle features that are difficult to detect with the most common test methods.

Understanding that children with ADHD have so many biologically based differences suggests that one action-based test is not enough to make a meaningful diagnosis of ADHD, the researchers found. say.

“ADHD is not just the child who moves and rests in a chair. It is also the child who is unconscious due to the break of day. Even though that child is more immigrant and that it doesn’t show as many symptoms as a depressed child, that doesn’t mean that child doesn’t suffer, “Ging-Jehli said. Daydreaming is especially common in girls, who are not recorded in ADHD studies almost as often as boys, she said.

Ging-Jehli described computer psychology as a tool that could also take note – continuing the symbolism – of mechanical differences in the car, and how this could affect driver behavior. . These dinamics can make ADHD more difficult to understand, but also open the door to a wider range of treatment options.

“We need to describe the different types of drivers and we need to understand the different situations we are exposed to. Based on just one observation, we cannot make decisions regarding diagnosis and treatment options,” “she said.

“However, cognitive testing and computer modeling should not be seen as an attempt to replace clinical interviews and questionnaire-based methods, but as support that adds value by providing new information.”

According to the researchers, a battery of tasks that measure social and mental characteristics should be assigned to a diagnosis rather than just one, and greater consistency across studies is needed to ensure that the same activities are used to assess the relevant cognitive concepts.

Finally, combining cognitive tests with psychiatric tests – specifically eye-tracking and EEG that record electrical activity in the brain – could provide powerful and measurable data to better diagnose help trustees and clinicians to better predict which medications would be most effective.

Ging-Jehli is testing these recommendations in her own research, applying a computer model in the study of specific neurological interventions in children with ADHD.

The purpose of our analysis was to show that there is a lack of consistency and so much complexity, and it is difficult to measure the symptoms with the available tools. We need to better understand ADHD so that children and adults have a better quality of life and receive the most appropriate treatment. “

Nadja Ging-Jehli, Lead study author of the Review and Graduate Student in Psychology, Ohio State University